Ramoelo, AbelMunyati, CLück-Vogel, MelanieLe Maitre, David CVan Aardt, J2009-12-102009-12-102007-09Ramoelo, A, Munyati, C and Vogel, M. 2007. Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing. Arid Zone Ecology Forum (AZEF) Conference. Sutherland, South Africa, 10 - 13 September 2007, pp 1http://hdl.handle.net/10204/3827This is a poster presentation, presented at the Arid Zone Ecology Forum (AZEF) Conference. Sutherland, South Africa from the 10th - 13th of September 2007.Land degradation is of great concern in South Africa particularly in the Inkomati catchment. Here a mosaic of different land use types such as plantation agriculture, subsistence farming, irrigated commercial farming, rural and urban settlements, as well as nature conservation affect the natural ecosystems in different ways and magnitudes. The National Land Cover (NLC2000) project mapped degraded areas in the catchment, but the results lack a differentiation of magnitude of degradation. For modelling of benefit flows from ecosystems a distinction of areas that are heavily degraded in contrast to only slightly affected areas is necessary. Therefore within a research project of the CSIR a method shall be developed to refine the degradation information of the NLC2000. Preliminary results using remote sensing derived albedo data are presented. The result will be used for modelling ecosystem benefits and their flows, with degraded areas playing an obvious role in defining ecosystems benefitsenLand degradationEcosystemInkomati catchmentRemote sensingArid zone ecology forumNational land coverModelling ecosystemLand degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing.Conference PresentationRamoelo, A., Munyati, C., Lück-Vogel, M., Le Maitre, D. C., & Van Aardt, J. (2007). Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing. http://hdl.handle.net/10204/3827Ramoelo, Abel, C Munyati, Melanie Lück-Vogel, David C Le Maitre, and J Van Aardt. "Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing." (2007): http://hdl.handle.net/10204/3827Ramoelo A, Munyati C, Lück-Vogel M, Le Maitre DC, Van Aardt J, Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing; 2007. http://hdl.handle.net/10204/3827 .TY - Conference Presentation AU - Ramoelo, Abel AU - Munyati, C AU - Lück-Vogel, Melanie AU - Le Maitre, David C AU - Van Aardt, J AB - Land degradation is of great concern in South Africa particularly in the Inkomati catchment. Here a mosaic of different land use types such as plantation agriculture, subsistence farming, irrigated commercial farming, rural and urban settlements, as well as nature conservation affect the natural ecosystems in different ways and magnitudes. The National Land Cover (NLC2000) project mapped degraded areas in the catchment, but the results lack a differentiation of magnitude of degradation. For modelling of benefit flows from ecosystems a distinction of areas that are heavily degraded in contrast to only slightly affected areas is necessary. Therefore within a research project of the CSIR a method shall be developed to refine the degradation information of the NLC2000. Preliminary results using remote sensing derived albedo data are presented. The result will be used for modelling ecosystem benefits and their flows, with degraded areas playing an obvious role in defining ecosystems benefits DA - 2007-09 DB - ResearchSpace DP - CSIR KW - Land degradation KW - Ecosystem KW - Inkomati catchment KW - Remote sensing KW - Arid zone ecology forum KW - National land cover KW - Modelling ecosystem LK - https://researchspace.csir.co.za PY - 2007 T1 - Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing TI - Land degradation mapping for modelling of ecosystem benefit flows in the Inkomati catchment using remote sensing UR - http://hdl.handle.net/10204/3827 ER -